Background Nurses play a vital role in pressure injury prevention (PIP) but require
foundational knowledge to ensure appropriate PIP strategies are enacted. Aims To describe …

Despite the urgent need for an effective prediction model tailored to individual interests,
existing models have mainly been developed for the mean outcome, targeting average …

Purpose This study aims to examine the resilience of Peruvian startups during the COVID-19
pandemic using a framework proposed by Lengnick-Hall et al.(2011), in which resilience …

High-dimensional accelerated failure time (AFT) models are commonly used regression
models in survival analysis. Feature selection problem in high-dimensional AFT models is …

Feature screening has become an indispensable statistical modeling tool for ultrahigh
dimensional data analysis. This article introduces a new model-free marginal feature …

Background Evidence of the clinical impact of programmed death-ligand 1 (PD-L1)
expression in small cell lung cancer (SCLC) is scarce and conflicting, even though …

Predictive models play a central role in decision making. Penalized regression approaches,
such as least absolute shrinkage and selection operator (LASSO), have been widely used to …

Purpose The risk of treatment-related toxicity is important for patients with localised prostate
cancer to consider when deciding between treatment options. We developed a model to …

We propose a model selection criterion for correlated survival data when the cluster size is
informative to the outcome. This approach, called Resampling Cluster Survival Information …

Feature selection for the high-dimensional Cox proportional hazards model (Cox model) is
very important in many microarray genetic studies. In this paper, we propose a sequential …